mlsanityData to 7 Oct 2026

Roadmap for Cybersecurity in Autonomous Vehicles

arXiv 2201.10349 ↗First posted 19 Jan 2022cs.CR cs.AI cs.LGcited by 5

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Abstract (arXiv)

Autonomous vehicles are on the horizon and will be transforming transportation safety and comfort. These vehicles will be connected to various external systems and utilize advanced embedded systems to perceive their environment and make intelligent decisions. However, this increased connectivity makes these vehicles vulnerable to various cyber-attacks that can have catastrophic effects. Attacks on automotive systems are already on the rise in today's vehicles and are expected to become more commonplace in future autonomous vehicles. Thus, there is a need to strengthen cybersecurity in future autonomous vehicles. In this article, we discuss major automotive cyber-attacks over the past decade and present state-of-the-art solutions that leverage artificial intelligence (AI). We propose a roadmap towards building secure autonomous vehicles and highlight key open challenges that need to be addressed.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 9 of its 42 references that are in the map. First posted on arXiv 19 Jan 2022.

Builds on

9 of 42 references.

References · 9

  1. 2020Knowledge-Enriched Distributional Model Inversion Attackscited by 65
  2. 2019GIDS: GAN based Intrusion Detection System for In-Vehicle Networkcited by 42
  3. 2019Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forwardcited by 33
  4. 2021Object Removal Attacks on LiDAR-based 3D Object Detectorscited by 15
  5. 2020INDRA: Intrusion Detection using Recurrent Autoencoders in Automotive Embedded Systemscited by 12
  6. 2021LATTE: LSTM Self-Attention based Anomaly Detection in Embedded Automotive Platformscited by 9
  7. 2021TENET: Temporal CNN with Attention for Anomaly Detection in Automotive Cyber-Physical Systemscited by 6
  8. 2021Resilient Cooperative Adaptive Cruise Control for Autonomous Vehicles Using Machine Learningcited by 3
  9. 2021Fortifying Vehicular Security Through Low Overhead Physically Unclonable Functionscited by 1

Built on by

Cited by year

Citing papers per year: 2022: 2; 2023: 1; 2024: 0; 2025: 2.

5 papers.